Development of Advanced Control Strategies for Grid-Interfacing Converters in Renewable Energy and EV Charging Applications
Model Predictive Control (MPC) is a control technique that has been gaining prominence in power electronics applications, such as battery chargers for electric vehicles. This PhD qualification text presents the partial results of applying MPC to a bidirectional DC/AC power converter on the grid side of an EV charger. The ultimate goal is to achieve a high degree of vehicle-to-grid power regulation with low harmonic distortion injected into the grid, while ensuring robust operation against internal and external disturbances.
The proposed system includes a power converter on the three-phase grid side, with battery charging emulated by a programmable source connected to the DC bus. Designing MPC in the vector space is one of the main challenges of the PhD project, which has been addressed through extensive literature research, simulations, and experimental bench tests. The final version of the doctoral thesis will also consider analyzing the control system's robustness in the presence of parametric uncertainties and grid voltage distortions.
The studies within this project aim to contribute to the efficient transition to electric mobility and the development of distributed energy resources in future smart grids.